Value of Triage Treatment Strategies to Distribute Hepatitis C Direct-Acting Antiviral Agents in an Integrated Healthcare System: A Cost-Effectiveness Analysis.

OBJECTIVES: This study aimed to assess the cost-effectiveness of fibrosis-based direct-acting antiviral treatment policies for patients with chronic hepatitis C virus at the Kaiser Permanente Mid-Atlantic States health system. METHODS: We used a Markov model to compare the lifetime costs and effects of treating patients with chronic hepatitis C virus at different stages of disease severity, or all stages simultaneously, based on a fibrosis score from the US healthcare sector perspective and societal perspective. The initial distribution of patients across fibrosis scores, the effectiveness of direct-acting antiviral therapy, and follow-up and monitoring protocols were specific to the Kaiser Permanente Mid-Atlantic States health system. Direct and indirect costs, transition probabilities, and utilities were derived from the literature. Deterministic and probabilistic sensitivity analyses were performed to assess the robustness of our results. RESULTS: The "Treat All" option was dominant from both the societal and healthcare sector perspectives. The conclusion was robust in deterministic sensitivity analysis. The range of incremental costs between the less restrictive policies was small-the difference between the "Treat F1+" and the "Treat All" option was only $111 per person. Probabilistic sensitivity analyses showed, at both the $100 000/quality-adjusted life-year and $150 000/quality-adjusted life-year thresholds, there was a 70% chance that the "Treat All" option was more cost-effective than the "Treat F1+" option. CONCLUSIONS: We found that expanded treatment access is cost-effective and, in many cases, cost saving. Although our results are primarily applicable to a regional integrated healthcare system, it offers some direction to any healthcare setting faced with resource constraints in the face of highly priced drugs.

Patterns of Hospital Performance on the Hospital-Wide 30-Day Readmission Metric: Is the Playing Field Level?

BACKGROUND: Hospital performance on the 30-day hospital-wide readmission (HWR) metric as calculated by the Centers for Medicare and Medicaid Services (CMS) is currently reported as a quality measure. Focusing on patient-level factors may provide an incomplete picture of readmission risk at the hospital level to explain variations in hospital readmission rates. OBJECTIVE: To evaluate and quantify hospital-level characteristics that track with hospital performance on the current HWR metric. DESIGN: Retrospective cohort study. SETTING/PATIENTS: A total of 4785 US hospitals. METRICS: We linked publically available data on individual hospitals published by CMS on patient-level adjusted 30-day HWR rates from July 1, 2011, through June 30, 2014, to the 2014 American Hospital Association annual survey. Primary outcome was performance in the worst CMS-calculated HWR quartile. Primary hospital-level exposure variables were defined as: size (total number of beds), safety net status (top quartile of disproportionate share), academic status [member of the Association of American Medical Colleges (AAMC)], National Cancer Institute Comprehensive Cancer Center (NCI-CCC) status, and hospital services offered (e.g., transplant, hospice, emergency department). Multilevel regression was used to evaluate the association between 30-day HWR and the hospital-level factors. RESULTS: Hospital-level characteristics significantly associated with performing in the worst CMS-calculated HWR quartile included: safety net status [adjusted odds ratio (aOR) 1.99, 95% confidence interval (95% CI) 1.61-2.45, p < 0.001], large size (> 400 beds, aOR 1.42, 95% CI 1.07-1.90, p = 0.016), AAMC alone status (aOR 1.95, 95% CI 1.35-2.83, p < 0.001), and AAMC plus NCI-CCC status (aOR 5.16, 95% CI 2.58-10.31, p < 0.001). Hospitals with more critical care beds (aOR 1.26, 95% CI 1.02-1.56, p = 0.033), those with transplant services (aOR 2.80, 95% CI 1.48-5.31,p = 0.001), and those with emergency room services (aOR 3.37, 95% CI 1.12-10.15, p = 0.031) demonstrated significantly worse HWR performance. Hospice service (aOR 0.64, 95% CI 0.50-0.82, p < 0.001) and having a higher proportion of total discharges being surgical cases (aOR 0.62, 95% CI 0.50-0.76, p < 0.001) were associated with better performance. LIMITATION: The study approach was not intended to be an alternate readmission metric to compete with the existing CMS metric, which would require a re-examination of patient-level data combined with hospital-level data. CONCLUSION: A number of hospital-level characteristics (such as academic tertiary care center status) were significantly associated with worse performance on the CMS-calculated HWR metric, which may have important health policy implications. Until the reasons for readmission variability can be addressed, reporting the current HWR metric as an indicator of hospital quality should be reevaluated.

Individualized cost-effectiveness analysis of patient-centered care: a case series of hospitalized patient preferences departing from practice-based guidelines.

OBJECTIVE: To develop cases of preference-sensitive care and analyze the individualized cost-effectiveness of respecting patient preference compared to guidelines. METHODS: Four cases were analyzed comparing patient preference to guidelines: (a) high-risk cancer patient preferring to forgo colonoscopy; (b) decubitus patient preferring to forgo air-fluidized bed use; (c) anemic patient preferring to forgo transfusion; (d) end-of-life patient requesting all resuscitative measures. Decision trees were modeled to analyze cost-effectiveness of alternative treatments that respect preference compared to guidelines in USD per quality-adjusted life year (QALY) at a $100,000/QALY willingness-to-pay threshold from patient, provider and societal perspectives. RESULTS: Forgoing colonoscopy dominates colonoscopy from patient, provider, and societal perspectives. Forgoing transfusion and air-fluidized bed are cost-effective from all three perspectives. Palliative care is cost-effective from provider and societal perspectives, but not from the patient perspective. CONCLUSION: Prioritizing incorporation of patient preferences within guidelines holds good value and should be prioritized when developing new guidelines.